(a) Field of the Invention
The present invention relates to an inference engine, and more particularly relates to a method for generating a decision tree by adaptively inferring desired results based on a current situation by using an inference engine in a ubiquitous environment.
(b) Description of the Related Art
In general, knowledge systems including an expert system emulate inference performed by an expert. The knowledge system typically uses an inference engine to interpret an expert's knowledge that is encoded and stored in a knowledge base. In addition, the expert system uses the expert's knowledge to solve difficult problems, and the inference engine is a core part of the expert system.
To infer a low data context sensed by a plurality of sensors in the knowledge system and input it to the knowledge system, reasoning mechanisms including a first order logic, a temporal logic, and a fuzzy logic, or learning mechanisms including a Bayesian network, a neural network, and a reinforcement learning have been conventionally used. The above mechanisms have problems of speed and memory in a mobile communication ubiquitous environment. Particularly, when a new sensor is additionally provided to a knowledge system, various problems and limited conditions may occur.
In addition, an algorithm C4.5 that is widely used to generate a decision tree of the inference engine may process an unknown value (i.e., a missing value). However, when a data event set additionally having a new attribute is input to the system, it has no appropriate solution for processing the unknown value.
The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.